"""
战略层智能体

实现战略决策层的智能体，包括CIO、投资决策委员会、董事会代表。
"""

from typing import Dict, List, Any, Optional
from datetime import datetime
from dataclasses import dataclass

from .base_agent import BaseAgent
from .agent_roles import AgentRole, AgentCapability
from ..coordination.coordination_patterns import CoordinationContext, CoordinationMode


@dataclass
class StrategicDecision:
    """战略决策"""
    decision_id: str
    decision_type: str  # 投资策略、风险政策、资产配置等
    description: str
    rationale: str
    impact_assessment: Dict[str, Any]
    approval_level: str
    created_by: str
    created_at: datetime
    effective_date: datetime
    review_date: Optional[datetime] = None
    status: str = "pending"  # pending, approved, rejected, implemented


class StrategicAgent(BaseAgent):
    """战略层智能体基类"""
    
    def __init__(self, agent_id: str, role: AgentRole):
        """
        初始化战略层智能体
        
        Args:
            agent_id: 智能体ID
            role: 智能体角色
        """
        super().__init__(agent_id, role)
        self._strategic_decisions: List[StrategicDecision] = []
        self._governance_rules: Dict[str, Any] = {}
        self._risk_tolerance: Dict[str, float] = {}
    
    async def make_strategic_decision(
        self,
        decision_type: str,
        context: Dict[str, Any]
    ) -> StrategicDecision:
        """
        制定战略决策
        
        Args:
            decision_type: 决策类型
            context: 决策上下文
            
        Returns:
            战略决策
        """
        # 基础实现，子类应重写此方法
        decision = StrategicDecision(
            decision_id=f"SD_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            decision_type=decision_type,
            description=f"战略决策: {decision_type}",
            rationale="基于当前市场环境和组织目标",
            impact_assessment={"risk_level": "medium", "expected_return": 0.0},
            approval_level=self.role.value,
            created_by=self.agent_id,
            created_at=datetime.now(),
            effective_date=datetime.now()
        )
        
        self._strategic_decisions.append(decision)
        return decision
    
    async def review_decision(self, decision_id: str) -> Dict[str, Any]:
        """
        审查决策
        
        Args:
            decision_id: 决策ID
            
        Returns:
            审查结果
        """
        decision = next(
            (d for d in self._strategic_decisions if d.decision_id == decision_id),
            None
        )
        
        if not decision:
            return {"status": "error", "message": "决策不存在"}
        
        # 基础审查逻辑
        review_result = {
            "decision_id": decision_id,
            "reviewer": self.agent_id,
            "review_date": datetime.now(),
            "recommendation": "approve",  # approve, reject, modify
            "comments": "决策符合战略目标",
            "risk_assessment": "acceptable"
        }
        
        return review_result
    
    def get_strategic_decisions(self) -> List[StrategicDecision]:
        """获取战略决策列表"""
        return self._strategic_decisions.copy()


class CIOAgent(StrategicAgent):
    """首席投资官智能体"""
    
    def __init__(self, agent_id: str = "cio_001"):
        """初始化CIO智能体"""
        super().__init__(agent_id, AgentRole.CIO)
        self._investment_philosophy = "价值投资与量化分析相结合"
        self._portfolio_targets = {}
        self._risk_budgets = {}
    
    async def process_task(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """
        处理任务
        
        Args:
            task: 任务信息
            
        Returns:
            处理结果
        """
        task_type = task.get("type", "")
        
        if task_type == "investment_strategy":
            return await self._develop_investment_strategy(task)
        elif task_type == "portfolio_allocation":
            return await self._set_portfolio_allocation(task)
        elif task_type == "risk_management":
            return await self._set_risk_policy(task)
        else:
            return await super().process_task(task)
    
    async def _develop_investment_strategy(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """制定投资策略"""
        market_outlook = task.get("market_outlook", {})
        time_horizon = task.get("time_horizon", "1年")
        
        strategy = {
            "strategy_id": f"IS_{datetime.now().strftime('%Y%m%d')}",
            "time_horizon": time_horizon,
            "market_view": market_outlook,
            "asset_allocation": {
                "equity": 0.6,
                "fixed_income": 0.3,
                "alternatives": 0.1
            },
            "investment_themes": [
                "科技创新",
                "绿色能源",
                "消费升级"
            ],
            "risk_target": {
                "max_drawdown": 0.15,
                "volatility_target": 0.12
            }
        }
        
        # 创建战略决策记录
        decision = await self.make_strategic_decision(
            "investment_strategy",
            {"strategy": strategy, "context": task}
        )
        
        return {
            "status": "success",
            "strategy": strategy,
            "decision_id": decision.decision_id
        }
    
    async def _set_portfolio_allocation(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """设定投资组合配置"""
        target_allocation = task.get("target_allocation", {})
        
        allocation = {
            "allocation_id": f"PA_{datetime.now().strftime('%Y%m%d')}",
            "target_weights": target_allocation,
            "rebalancing_frequency": "月度",
            "tolerance_bands": {
                asset: 0.05 for asset in target_allocation.keys()
            },
            "implementation_timeline": "2周内完成"
        }
        
        decision = await self.make_strategic_decision(
            "portfolio_allocation",
            {"allocation": allocation, "context": task}
        )
        
        return {
            "status": "success",
            "allocation": allocation,
            "decision_id": decision.decision_id
        }
    
    async def _set_risk_policy(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """设定风险政策"""
        risk_parameters = task.get("risk_parameters", {})
        
        policy = {
            "policy_id": f"RP_{datetime.now().strftime('%Y%m%d')}",
            "risk_limits": {
                "var_limit": risk_parameters.get("var_limit", 0.02),
                "concentration_limit": risk_parameters.get("concentration_limit", 0.1),
                "leverage_limit": risk_parameters.get("leverage_limit", 2.0)
            },
            "stress_test_scenarios": [
                "市场崩盘",
                "利率急升",
                "流动性危机"
            ],
            "escalation_procedures": {
                "warning_threshold": 0.8,
                "breach_threshold": 1.0,
                "emergency_contacts": ["risk_manager", "compliance_officer"]
            }
        }
        
        decision = await self.make_strategic_decision(
            "risk_policy",
            {"policy": policy, "context": task}
        )
        
        return {
            "status": "success",
            "policy": policy,
            "decision_id": decision.decision_id
        }


class InvestmentCommitteeAgent(StrategicAgent):
    """投资决策委员会智能体"""
    
    def __init__(self, agent_id: str = "ic_001"):
        """初始化投资委员会智能体"""
        super().__init__(agent_id, AgentRole.INVESTMENT_COMMITTEE)
        self._committee_members = []
        self._voting_rules = {}
        self._meeting_schedule = {}
    
    async def process_task(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """
        处理任务
        
        Args:
            task: 任务信息
            
        Returns:
            处理结果
        """
        task_type = task.get("type", "")
        
        if task_type == "decision_review":
            return await self._review_strategic_decision(task)
        elif task_type == "policy_approval":
            return await self._approve_policy(task)
        elif task_type == "performance_review":
            return await self._review_performance(task)
        else:
            return await super().process_task(task)
    
    async def _review_strategic_decision(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """审查战略决策"""
        decision_data = task.get("decision", {})
        
        # 模拟委员会审议过程
        review_criteria = [
            "战略一致性",
            "风险可控性",
            "预期收益",
            "实施可行性"
        ]
        
        scores = {}
        for criterion in review_criteria:
            # 模拟评分（实际应基于具体分析）
            scores[criterion] = 8.5  # 满分10分
        
        overall_score = sum(scores.values()) / len(scores)
        recommendation = "approve" if overall_score >= 7.0 else "reject"
        
        review_result = {
            "review_id": f"CR_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "decision_id": decision_data.get("decision_id"),
            "review_criteria": review_criteria,
            "scores": scores,
            "overall_score": overall_score,
            "recommendation": recommendation,
            "comments": "决策经过充分论证，符合投资目标",
            "conditions": [] if recommendation == "approve" else ["需要进一步风险评估"]
        }
        
        return {
            "status": "success",
            "review": review_result
        }
    
    async def _approve_policy(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """批准政策"""
        policy_data = task.get("policy", {})
        
        approval = {
            "approval_id": f"AP_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "policy_id": policy_data.get("policy_id"),
            "approval_status": "approved",
            "effective_date": datetime.now(),
            "review_period": "季度",
            "approved_by": self.agent_id,
            "conditions": [
                "需要定期监控执行效果",
                "如有重大市场变化需及时调整"
            ]
        }
        
        return {
            "status": "success",
            "approval": approval
        }
    
    async def _review_performance(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """审查业绩表现"""
        performance_data = task.get("performance", {})
        
        review = {
            "review_id": f"PR_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "period": performance_data.get("period", "月度"),
            "key_metrics": {
                "return": performance_data.get("return", 0.0),
                "volatility": performance_data.get("volatility", 0.0),
                "sharpe_ratio": performance_data.get("sharpe_ratio", 0.0),
                "max_drawdown": performance_data.get("max_drawdown", 0.0)
            },
            "benchmark_comparison": {
                "relative_return": 0.02,  # 超额收益
                "tracking_error": 0.03
            },
            "assessment": "表现符合预期",
            "recommendations": [
                "继续执行当前策略",
                "关注市场风险变化"
            ]
        }
        
        return {
            "status": "success",
            "review": review
        }


class BoardRepresentativeAgent(StrategicAgent):
    """董事会代表智能体"""
    
    def __init__(self, agent_id: str = "board_001"):
        """初始化董事会代表智能体"""
        super().__init__(agent_id, AgentRole.BOARD_REPRESENTATIVE)
        self._governance_framework = {}
        self._compliance_requirements = []
        self._stakeholder_interests = {}
    
    async def process_task(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """
        处理任务
        
        Args:
            task: 任务信息
            
        Returns:
            处理结果
        """
        task_type = task.get("type", "")
        
        if task_type == "governance_oversight":
            return await self._provide_governance_oversight(task)
        elif task_type == "compliance_review":
            return await self._review_compliance(task)
        elif task_type == "stakeholder_communication":
            return await self._communicate_with_stakeholders(task)
        else:
            return await super().process_task(task)
    
    async def _provide_governance_oversight(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """提供治理监督"""
        oversight_area = task.get("area", "")
        
        oversight = {
            "oversight_id": f"GO_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "area": oversight_area,
            "findings": [
                "投资决策流程规范",
                "风险控制措施有效",
                "信息披露及时透明"
            ],
            "recommendations": [
                "加强ESG投资考量",
                "完善数字化治理工具",
                "提升决策透明度"
            ],
            "compliance_status": "符合监管要求",
            "next_review_date": "下季度"
        }
        
        return {
            "status": "success",
            "oversight": oversight
        }
    
    async def _review_compliance(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """审查合规性"""
        compliance_area = task.get("area", "")
        
        review = {
            "review_id": f"CR_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "compliance_area": compliance_area,
            "regulatory_requirements": [
                "投资者适当性管理",
                "信息披露义务",
                "风险管理要求"
            ],
            "compliance_status": "合规",
            "identified_risks": [
                "监管政策变化风险",
                "操作合规风险"
            ],
            "mitigation_measures": [
                "建立合规监控系统",
                "定期合规培训",
                "完善内控制度"
            ]
        }
        
        return {
            "status": "success",
            "review": review
        }
    
    async def _communicate_with_stakeholders(self, task: Dict[str, Any]) -> Dict[str, Any]:
        """与利益相关者沟通"""
        stakeholder_type = task.get("stakeholder_type", "")
        message_content = task.get("message", {})
        
        communication = {
            "communication_id": f"SC_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "stakeholder_type": stakeholder_type,
            "message_summary": message_content.get("summary", ""),
            "key_points": [
                "投资业绩稳健",
                "风险控制有效",
                "战略执行顺利"
            ],
            "delivery_channels": [
                "定期报告",
                "投资者会议",
                "官方公告"
            ],
            "feedback_mechanism": "问卷调查和直接沟通",
            "follow_up_actions": [
                "收集反馈意见",
                "调整沟通策略"
            ]
        }
        
        return {
            "status": "success",
            "communication": communication
        }